1) Copy.Reverse engineer the underlying generative AI model and its associated data4) Direct UseRecord the competing generative AI outputs and feed those as training for your generative AIFind recorded competing generative AI outputs and feed those as training for your generative AIIn the case of copying a competing generative AI model and its associated data, such an act is likely to invoke all manner of legal consternations .
This would not appear to raise any notable legal conundrums, though there are possibilities such as some might contend that this could come under anti-trust or other legally peripheral concerns. The approach might be likened to car makers that buy a competing car and drive it around their test track. They do so to see what the competition can do. It might then be compared to their own products and possibly spur new ideas of additional features or future changes to their automobiles.
You might not know that in the specific case of trying to use ChatGPT for such a purpose, the OpenAI licensing says that you cannot do this. There is a declarative statement that indicates you aren’t allowed to use ChatGPT to develop AI models that compete with OpenAI. The difference between this approach and the one above that wires up two generative AI apps is that you can use the recorded outputs at your leisure. The two generative AI apps aren’t working in real-time on a head-to-head basis. Instead, you record the outputs of the competing generative AI and later on feed those into your generative AI.
You could try to find recorded outputs from a competing generative AI app that has perchance been posted on the Internet. In this instance, you would be able to point out that you did not directly use the competing generative AI app. Other people did so. Those people posted their generated outputs. All you did was happen to scan those posted outputs and then used those postings to aid in data training of your generative AI.